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Highly energetic rockfalls: back analysis of the 2015 event from the Mel de la Niva, Switzerland.

Authors :
Noël, François
Nordang, Synnøve Flugekvam
Jaboyedoff, Michel
Travelletti, Julien
Matasci, Battista
Digout, Michaël
Derron, Marc-Henri
Caviezel, Andrin
Hibert, Clément
Toe, David
Talib, Miloud
Wyser, Emmanuel
Bourrier, Franck
Toussaint, Renaud
Malet, Jean-Philippe
Locat, Jacques
Source :
Landslides; Aug2023, Vol. 20 Issue 8, p1561-1582, 22p
Publication Year :
2023

Abstract

Process-based rockfall simulation models attempt to better emulate rockfall dynamics to different degrees. As no model is perfect, their development is often accompanied and validated by the valuable collection of rockfall databases covering a range of site geometries, rock masses, velocities, and related energies that the models are designed for. Additionally, such rockfall data can serve as a base for assessing the model's sensitivity to different parameters, evaluating their predictability and helping calibrate the model's parameters from back calculation and analyses. As the involved rock volumes/masses increase, the complexity of conducting field-test experiments to build up rockfall databases increases to a point where such experiments become impracticable. To the author's knowledge, none have reconstructed rockfall data in 3D from real events involving block fragments of approximately 500 metric tons. A back analysis of the 2015 Mel de la Niva rockfall event is performed in this paper, contributing to a novel documentation in terms of kinetic energy values, bounce heights, velocities, and 3D lateral deviations of these rare events involving block fragments of approximately 200 m<superscript>3</superscript>. Rockfall simulations are then performed on a "per-impact" basis to illustrate how the reconstructed data from the site can be used to validate results from simulation models. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
ROCKFALL
KINETIC energy

Details

Language :
English
ISSN :
1612510X
Volume :
20
Issue :
8
Database :
Complementary Index
Journal :
Landslides
Publication Type :
Academic Journal
Accession number :
164799723
Full Text :
https://doi.org/10.1007/s10346-023-02054-2